DEVELOPMENT OF NEURAL SIGNAL CONTROL SYSTEM--TOWARD INTELLIGENT TRAFFIC SIGNAL CONTROL

Abstract

This study describes the process of developing a traffic signal control for isolated intersections using artificial neural networks. Currently existing signal control systems are briefly discussed and their shortcomings presented. Subsequently, a new multilayered neural network architecture is presented that diminishes many of the shortcomings in existing controllers. The new control system, called neural signal control system (NSCS), is more adaptive to the changes in traffic patterns that take place at isolated intersections. It also provides the traffic engineer more flexibility in terms of optimizing different measures of effectiveness. After describing the architecture and operation of this new system, a comparative analysis is performed by simulating different traffic patterns at a hypothetical intersection using both NSCS and a commonly used software--signal operations analysis package (SOAP). Measures of effectiveness produced by both NSCS and SOAP indicate NSCS's superiority in all aspects. This study concludes with some thoughts for further research in this area.